Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.
|Author||Daniel F. Schmidt [aut, cph, cre] (<https://orcid.org/0000-0002-1788-2375>), Enes Makalic [aut, cph] (<https://orcid.org/0000-0003-3017-0871>)|
|Maintainer||Daniel F. Schmidt <firstname.lastname@example.org>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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